Triple
T12955705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Foursquare |
E310004
|
entity |
| Predicate | hasTypicalLayout |
P10827
|
FINISHED |
| Object | four-room floor plan per level |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: four-room floor plan per level | Statement: [American Foursquare, hasTypicalLayout, four-room floor plan per level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalLayout Context triple: [American Foursquare, hasTypicalLayout, four-room floor plan per level]
-
A.
hasLayout
chosen
Indicates that one entity defines or is associated with the structural arrangement or organization (layout) of another entity.
-
B.
isTypicallyLayered
Indicates that something is usually composed of multiple distinct layers arranged one on top of another.
-
C.
hasLandscapeType
Indicates that an entity possesses or is characterized by a particular type or category of landscape.
-
D.
hasLayoutElement
Indicates that one entity includes, contains, or is associated with a specific layout element as part of its structural or visual arrangement.
-
E.
hasTypicalPlan
Indicates that there is a standard or commonly followed plan, procedure, or course of action typically associated with the given entity or situation.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:44 p.m.